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Permafrost Carbon Cycle Observations and Modeling .. (PERCCOM)
Permafrost Carbon Cycle Observations and Modeling across multiple spatiotemporal scales
(PERCCOM)
Date du début: 1 mars 2013,
Date de fin: 28 févr. 2017
PROJET
TERMINÉ
Permafrost ecosystems in the high Northern latitudes are estimated to store about 1700 Petagram of carbon, which is roughly 50% of the total global belowground carbon, or about double the amount currently contained in the global atmosphere. Future climate projections indicate a strong warming potential for these regions over the next century, which may significantly alter the biogeochemical processes governing the carbon cycle, and thus holds the potential to partly destabilize and release these enormous existing carbon reservoirs. At the same time, the database on carbon exchange fluxes between surface and atmosphere is sparse compared to the size of the region, and significant gaps exist concerning e.g. the coverage of specific landscape units, or observations during the cold season. As a consequence, many processes within the permafrost carbon cycle remain poorly understood, leading to large uncertainties in climate model simulations for this region.To close existing gaps in both flux Arctic flux databases and process understanding, integrated monitoring and modeling tools are required that provide insight into feedback mechanisms between permafrost ecosystems and climate change. This project will establish year-round observation systems in the permafrost region that integrate over multiple spatiotemporal scales to capture carbon flux variability from local to continental levels. The obtained information will be used to identify causal links between environmental drivers and patterns in carbon fluxes based on an integrated framework of atmospheric transport modeling, multivariate statistics, geostatistical inversion and biogeochemical process modeling. The resulting insights into biogeochemical mechanisms will help to improve process representation in modeling frameworks, with the overarching objective to reduce uncertainties in climate projections.
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